// Arguments: Doubles, Doubles, Ints, Doubles, Doubles
#include <stan/math/prim.hpp>

using stan::math::var;
using std::numeric_limits;
using std::vector;

class AgradDistributionNormalSufficient : public AgradDistributionTest {
 public:
  void valid_values(vector<vector<double> >& parameters,
                    vector<double>& log_prob) {
    vector<double> param(5);

    // observed values: -0.1, 0.1
    param[0] = 0;     // y_bar
    param[1] = 0.02;  // s_squared
    param[2] = 2;     // n_obs
    param[3] = -2.3;  // mu
    param[4] = 2.1;   // sigma
    parameters.push_back(param);
    log_prob.push_back(-4.52356581482502);  // expected log_prob

    // observed values: 0, 1
    param[0] = 0.5;  // y_bar
    param[1] = 0.5;  // s_squared
    param[2] = 2;    // n_obs
    param[3] = 0;    // mu
    param[4] = 1;    // sigma
    parameters.push_back(param);
    log_prob.push_back(-2.33787706640935);  // expected log_prob

    // observed values: 0, 2
    param[0] = 1;  // y_bar
    param[1] = 2;  // s_squared
    param[2] = 2;  // n_obs
    param[3] = 1;  // mu
    param[4] = 1;  // sigma
    parameters.push_back(param);
    log_prob.push_back(-2.83787706640935);  // expected log_prob

    // observed values: 1, 2
    param[0] = 1.5;  // y_bar
    param[1] = 0.5;  // s_squared
    param[2] = 2;    // n_obs
    param[3] = -1;   // mu
    param[4] = 3;    // sigma
    parameters.push_back(param);
    log_prob.push_back(-4.75732386596779);  // expected log_prob
  }

  void invalid_values(vector<size_t>& index, vector<double>& value) {
    // y

    // mu
    index.push_back(3U);
    value.push_back(numeric_limits<double>::infinity());

    index.push_back(3U);
    value.push_back(-numeric_limits<double>::infinity());

    // sigma
    index.push_back(4U);
    value.push_back(0.0);

    index.push_back(4U);
    value.push_back(-1.0);

    index.push_back(4U);
    value.push_back(-numeric_limits<double>::infinity());
  }

  template <typename T_y, typename T_s, typename T_n, typename T_loc,
            typename T_scale, typename T5>
  stan::return_type_t<T_y, T_s, T_n, T_loc, T_scale> log_prob(
      const T_y& y_bar, const T_s& s_squared, const T_n& n_obs, const T_loc& mu,
      const T_scale& sigma, const T5&) {
    return stan::math::normal_sufficient_lpdf(y_bar, s_squared, n_obs, mu,
                                              sigma);
  }

  template <bool propto, typename T_y, typename T_s, typename T_n,
            typename T_loc, typename T_scale, typename T5>
  stan::return_type_t<T_y, T_s, T_n, T_loc, T_scale> log_prob(
      const T_y& y_bar, const T_s& s_squared, const T_n& n_obs, const T_loc& mu,
      const T_scale& sigma, const T5&) {
    return stan::math::normal_sufficient_lpdf<propto>(y_bar, s_squared, n_obs,
                                                      mu, sigma);
  }

  template <typename T_y, typename T_s, typename T_n, typename T_loc,
            typename T_scale, typename T5>
  stan::return_type_t<T_y, T_s, T_n, T_loc, T_scale> log_prob_function(
      const T_y& y_bar, const T_s& s_squared, const T_n& n_obs, const T_loc& mu,
      const T_scale& sigma, const T5&) {
    using stan::math::include_summand;
    using stan::math::pi;
    using stan::math::square;
    stan::return_type_t<T_y, T_s, T_n, T_loc, T_scale> lp(0.0);
    if (include_summand<true, T_scale>::value)
      lp -= n_obs * log(sigma);

    lp -= (s_squared + n_obs * pow(y_bar - mu, 2)) / (2 * pow(sigma, 2));

    if (include_summand<true>::value)
      lp -= log(sqrt(2.0 * pi()));
    return lp;
  }
};
